This invention relates to image enhancement techniques, and especially to image enhancement by histogram modification. More specifically, the invention is directed to histogram modification of a still video picture which technique can be applied to advantage in medical or veterinary use, to-wit, in digital computerized fluoroscopy or the like.
The field of digital video radiography has recently received much attention as a clinical procedure, particularly for its advantages over the traditional silver-halide film techniques. The new techniques include digital subtraction angiography and digital computerized fluoroscopy. In both of these techniques a low-power x-ray tube radiates through a patient's body tissues to a phosphor plate or other image producing device, usually forming a part of an image intensifier. A high-resolution video camera is focused at the image formed by the image intensifier. The camera produces a still picture signal which is digitized and stored in a computer memory. Subtraction radiography employs a similar procedure, but a second exposure is taken and the difference values of the two resulting still images are stored and processed.
There are at least two problem areas that must be addressed by digital video radiography, namely, optimizing image spatial resolution and contrast quality, and reducing x-ray exposure to the patient and to the radiologist.
The problem of poor image quality and loss of low-contrast detail had to be solved to reduce or eliminate the need for retaking of images. Ideally, the images taken should be corrected and enhanced to show the necessary tissue detail, so that a patient need not be re-exposed to radiation. Also, the ability to reliably produce ideal video images, and to eliminate the need to retake radiographs, frees the equipment and radiology personnel for radiography on other patients.
One possible means to effect suitable image enhancement is with so-called histogram equalization. In this technique, the digitized video signal is stored in the form of luminance or brightness values for respective image pixels (picture elements). In the video pictures, the pixels are arrayed in a tableau. Each luminance value corresponds to a gray scale value from zero (black) to a maximum brightness (white). In a poor-quality picture, the values are all concentrated in one part of the gray scale. For a severely underexposed video picture, for example, most of the pixels will have low luminance values with little difference from one to another. This yields a picture with little visibility of detail. The objective of histogram equalization is to provide a transfer function on which the original digital video luminance values can be mapped to yield corresponding new values that extend over the entire gray scale, and thereby increase the contrast and image clarity.
The histogram equalization enhancement technique accumulates and tabulates the number of pixels of each gray scale level. A cumulative histogram is formed which accumulates the total of all pixels having a given gray scale value or below. This produces a monotonic-increasing transfer function which has a higher slope where there are more occurrences of gray scale information and a flat or low slope where there are few occurrences.
Histogram equalization techniques are described in Robert Hummel, "Image Enhancement by Histogram Transformation", Computer Graphics and Image Processing, Vol. 6, No. 2, 184-195, 1977; Jean Claude Simon and Azriel Rosenfeld, "Digital Image Processing and Analysis", Nato Advanced Study Series, Ser. E, No. 20, 47-53, 1977; J. Kautsky, N. Nichols and D. L. B. Jupp, "Smoothed Histogram Modification for Image Processing", Computer Graphics and Image Processing, Vol. 26, No. 3 271-291, June 1984; W. Frei, "Image Enhancement by Histogram Hyperbolization", Computer Graphics and Image Processing, Vol. 6, No. 3, 286-294, 1977; and U.S. Pat. Nos. 3,983,320; 4,365,304; and 4,445,138.
In these techniques, there is good contrast in the resulting picture, but there is a tendency to emphasize the center gray scale levels. The mapping is non-linear which tends to distort the original image's contrast relation, and very light or very dark areas lose emphasis. These low contrast areas, which are the high interest areas in many radiographs, often lack sufficient detail for reliable diagnosis.